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swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_11

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update model card README.md

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@@ -22,10 +22,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8566378633150039
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  - name: Precision
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  type: precision
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- value: 0.8916086530475995
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,12 +35,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5327
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- - Accuracy: 0.8566
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- - F1 Score: 0.8626
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- - Precision: 0.8916
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- - Sensitivity: 0.8582
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- - Specificity: 0.9636
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  ## Model description
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@@ -59,7 +59,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.001
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  - train_batch_size: 100
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  - eval_batch_size: 100
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision | Sensitivity | Specificity |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:-----------:|:-----------:|
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- | 1.2738 | 0.99 | 19 | 3.6805 | 0.3606 | 0.2878 | 0.6974 | 0.3569 | 0.8381 |
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- | 0.8184 | 1.97 | 38 | 2.2141 | 0.5196 | 0.4842 | 0.8085 | 0.5311 | 0.8793 |
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- | 0.3966 | 2.96 | 57 | 0.6808 | 0.8009 | 0.7976 | 0.8463 | 0.8029 | 0.9491 |
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- | 0.2336 | 4.0 | 77 | 0.5914 | 0.7946 | 0.8011 | 0.8170 | 0.7978 | 0.9461 |
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- | 0.1196 | 4.99 | 96 | 0.4851 | 0.8606 | 0.8606 | 0.8779 | 0.8645 | 0.9644 |
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- | 0.1003 | 5.97 | 115 | 0.5353 | 0.8413 | 0.8475 | 0.8716 | 0.8442 | 0.9593 |
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- | 0.0876 | 6.96 | 134 | 0.6691 | 0.8032 | 0.8151 | 0.8766 | 0.8051 | 0.9503 |
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- | 0.0569 | 8.0 | 154 | 0.4531 | 0.8570 | 0.8610 | 0.8776 | 0.8614 | 0.9634 |
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- | 0.0329 | 8.99 | 173 | 0.8581 | 0.7977 | 0.8081 | 0.8692 | 0.8023 | 0.9488 |
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- | 0.0262 | 9.87 | 190 | 0.5327 | 0.8566 | 0.8626 | 0.8916 | 0.8582 | 0.9636 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9752553024351924
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  - name: Precision
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  type: precision
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+ value: 0.9748580935041002
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0948
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+ - Accuracy: 0.9753
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+ - F1 Score: 0.9750
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+ - Precision: 0.9749
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+ - Sensitivity: 0.9753
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+ - Specificity: 0.9938
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 100
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  - eval_batch_size: 100
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision | Sensitivity | Specificity |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:-----------:|:-----------:|
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+ | 1.2367 | 0.99 | 19 | 0.3560 | 0.8649 | 0.8629 | 0.8649 | 0.8629 | 0.9648 |
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+ | 0.2911 | 1.97 | 38 | 0.2087 | 0.9297 | 0.9290 | 0.9335 | 0.9277 | 0.9822 |
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+ | 0.1681 | 2.96 | 57 | 0.1393 | 0.9564 | 0.9558 | 0.9558 | 0.9562 | 0.9890 |
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+ | 0.0923 | 4.0 | 77 | 0.1106 | 0.9643 | 0.9639 | 0.9637 | 0.9647 | 0.9910 |
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+ | 0.0602 | 4.99 | 96 | 0.1510 | 0.9505 | 0.9494 | 0.9512 | 0.9504 | 0.9875 |
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+ | 0.0388 | 5.97 | 115 | 0.1145 | 0.9666 | 0.9667 | 0.9670 | 0.9672 | 0.9916 |
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+ | 0.0197 | 6.96 | 134 | 0.0783 | 0.9800 | 0.9796 | 0.9797 | 0.9796 | 0.9950 |
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+ | 0.0172 | 8.0 | 154 | 0.1032 | 0.9713 | 0.9713 | 0.9715 | 0.9718 | 0.9928 |
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+ | 0.0169 | 8.99 | 173 | 0.0854 | 0.9776 | 0.9772 | 0.9771 | 0.9774 | 0.9944 |
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+ | 0.0104 | 9.87 | 190 | 0.0948 | 0.9753 | 0.9750 | 0.9749 | 0.9753 | 0.9938 |
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  ### Framework versions